Data Analyst, New Product Introduction, Energy

Tesla-posted 11 months ago
Full-time • Mid Level
Sparks, NV
5,001-10,000 employees
Motor Vehicle and Parts Dealers
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The Gigafactory New Product Introduction team in Nevada is looking for a Data Engineer to support Operations and Process teams. This position will support automation of production controls, value stream mapping, OEE (cycle time, yield rates, downtime) data collection, analysis, and visualization. The successful candidate will be able to engage with advanced statistics, automating data pipelines, maintaining respective databases, and creating live visualization tools to enable informed and quick decision making for Tesla Energy products.

  • Analyze operations, equipment, process, safety, and quality data and extract useful statistics and insights to drive meaningful improvements in overall productivity
  • Work effectively with Engineers and conduct end-to-end analyses, from data requirement gathering to data processing and modeling
  • Monitor key operations and process metrics, understanding root causes of changes
  • Interpret data, analyze results using statistical techniques and provide ongoing reports
  • Identify, analyze, and interpret trends or patterns in complex data sets and depict the story via dashboards and reports
  • Maintain existing data visualizations, data pipelines and dashboard enhancement requests
  • Acquire data from primary or secondary data sources and maintain databases/data systems to empower operational excellence
  • Perform data quality validations to ensure data creation is as per the business needs, expectations, and compliant with data confidentiality policies
  • Degree in Engineering, or equivalent experience
  • Experience with programming languages (Python, C+, MATLAB)
  • Experience with multiple data architecture paradigms (e.g. SQL, NoSQL, R)
  • Experience with dashboarding and data cleaning tools such as Tableau, QlikView, Power Bi, Alteryx
  • Familiarity with manufacturing systems such as SAP, MES, SCADA
  • Able to work under pressure while collaborating and managing competing demands with tight deadlines
  • Ability to drive introduction of predictive model to a production environment
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